fit.SpectraModel: Fits a calibration model for soil spectroscopy

In soil.spec: Soil Spectroscopy Tools and Reference Models

Description

Fits a calibration model that can be used to convert absorbances to soil properties. Implements the "plsr" function available from the pls package.

Usage

 
## S4 method for signature 'formula,SpectraPoints,data.frame'
fit(formulaString, sampled, reference, 
   idcol = "SAMPLEID", ab.r = get("MIR", envir=spec.opts), 
   CO2.band = get("CO2.band", envir=spec.opts), ncomp, ncomp.max=15, 
   repl = 5, segment.type = "interleaved", prefix = "X", ...)
## S4 method for signature 'list,SpectraPoints,data.frame'
fit(formulaString, sampled, reference, ...)

Arguments

formulaString	"formula"; formula string
sampled	"SpectraPoints"; absorbances
reference	"data.frame"; reference values estimated in laboratory using at the order of magnitude more precise technique
idcol	"character"; column with sample IDs
ab.r	"numeric"; natural range of wavenumbers of interest
CO2.band	"numeric"; range of wavenumbers for the CO2 band
ncomp	"integer"; number of components (if not specified will be determined using cross-validation)
ncomp.max	"integer"; maximum number of components to be used for model fitting
repl	"integer"; number of repetitions for "pls::plsr"
segment.type	"character"; segment type for "pls::plsr"
prefix	"character"; default prefix to be added to the band names
...	other optional arguments

Details

Returns an object of class "SpectraModel", which contains slots: (1) "variable" (variable name according to the global soil data registry), (2) "Space" (3D space defined by the 1–3 principal components for absorbances), and (3) "model" (fitted model; usually of type pls::plsr and as an output from the partial least squares regression). Fitting models for large data sets can be time and memory consuming.

Author(s)

Andrew Sila and Tomislav Hengl

References

• Mevik, B.-H., Wehrens, R. (2007) The pls Package: Principal Component and Partial Least Squares Regression in R. Journal of Statistical Software 18(2), 1-24.

• Africa Soil Information Service (http://africasoils.net)

See Also

predict.SpectraPoints, spec.opts

Examples

## Not run: 
## build a callibration model using AfSIS data:
library(plyr)
library(sp)
library(rgdal)

data(afss)
afss.tbl <- join(afss$sites, afss$horizons)
con <- url("http://gsif.isric.org/lib/exe/fetch.php?media=afss.spec.rda")
load(con)
afss.spec.ab <- Spectra(samples=data.frame(SAMPLEID=afss.spec$SAMPLEID, 
   MID="ICR_SOIL", DateTime=Sys.time()), ab=afss.spec)
sel.r <- !afss.tbl$LONWGS84==100
sp <- data.frame(afss.tbl[sel.r,c("LONWGS84","LATWGS84")])
coordinates(sp) <- ~LONWGS84+LATWGS84
proj4string(sp) <- CRS("+proj=longlat")
attr(sp@coords, "dimnames")[[1]] <- afss.tbl$SAMPLEID[sel.r]
## extend to SprectraPoints:
afss.spec.sp <- SpectraPoints(Spectra=afss.spec.ab, sp=sp)
## select bands of interest:
cutspec <- c(600,2350.8,2379.8,4000)
col.no <- sapply(names(afss.spec.sp@data@ab)[-1], 
   function(x){as.numeric(strsplit(x, "X")[[1]][2])})
sel <- col.no>cutspec[1] & col.no<cutspec[2] | 
       col.no>cutspec[3] & col.no<cutspec[4]
summary(sel)
formulaString <- as.formula(paste("na.omit(log(ORCDRC)) ~ ", 
   paste(names(afss.spec.sp@data@ab[-1])[sel], collapse="+")))
m.ORC <- fit(formulaString, sampled=afss.spec.sp, reference=afss.tbl) 
str(m.ORC)

## End(Not run)
## this model, in fact, is included in the package:
data(m.ORCCNS)
str(m.ORCCNS)

soil.spec documentation built on May 2, 2019, 6:08 p.m.